Based on the principle of the dimension chain, this paper studies the dimension chain mathematical model and chooses a reasonable method for calculation of the dimension chain, establishing a model of the calculation of dimension chain margin of computer aided analysis and calculation. On AutoCAD platform, we developed the dimension chain calculation analysis software through secondary development by VBA, and applied the technology to dimension chain margin check. This significant saves the time spent in the process of manually calculating the dimension chain.
Some problems existing in active standard of the shape tolerance and shape error assessment are geometrical problems which are based on the shape tolerance zone. This paper presents the probability distribution of the statistical cylinder error on the condition of the researching about cylinder error of rotor parts and does experimental measurement and data collection. It is proved that it complies with certain probability distribution law, the fitted cylinder error should gain the statistical distribution result by using mathematical statistics.
Degree-days are to normalise energy consumption data and furthermore can generate forecasting predictions for energy demand being used to compare between different properties across different location and years. The base temperature is the main factor to consider the accuracy of degree days. The aim of this study was to evaluate the impact of data granularity to understand its effect on a correlation between energy consumption and Degree Days. Degree Days were calculated using the standard 18.3 °C base temperature as taking in the United States of America and compare the Degree Days calculations against the calculation based on hourly, daily and monthly data for base temperature. The methodology followed is based on the analysis of 23 houses located in Texas, Austin. The properties under study are from different construction periods and with a variety of total floor areas. This study had demonstrated the effect of the granularity of the data collected to generate Degree Days and its impact on the correlation between energy consumption and degree-days for different base temperatures. While the higher correlations are achieved using a monthly granularity, this approach is not recommended due to the small number of data points and a much more preferred approach that should be taken is a daily approach, which would generate a much more reliable correlation. In this study, higher correlation values were achieved when using the standard 18.3 °C base temperature for the Degree Days calculations, 70 % correlation in daily approach versus 56.67 % using indoor temperature, showing better results across the board against the use of indoor temperature at all granularity levels.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.